This paper is in the following e-collection/theme issue:

Viewpoints and Perspectives (619) Artificial Intelligence (2129) Clinical Information and Decision Making (1915) Decision Support for Health Professionals (1539) Advanced Data Analytics in eHealth (209) Ethics, Privacy, and Legal Issues (617) E-Health Policy and Health Systems Innovation (341)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50295, first published .
Resilient Artificial Intelligence in Health: Synthesis and Research Agenda Toward Next-Generation Trustworthy Clinical Decision Support

Resilient Artificial Intelligence in Health: Synthesis and Research Agenda Toward Next-Generation Trustworthy Clinical Decision Support

Resilient Artificial Intelligence in Health: Synthesis and Research Agenda Toward Next-Generation Trustworthy Clinical Decision Support

Authors of this article:

Carlos Sáez1 Author Orcid Image ;   Pablo Ferri1 Author Orcid Image ;   Juan M García-Gómez1 Author Orcid Image
Article Authors Cited by (14) Tweetations (8) Metrics

Journals

  1. Singh A, Sharma K, Bajpai M, Sarasa-Cabezuelo A. Patient centric trustworthy AI in medical analysis and disease prediction: A Comprehensive survey and taxonomy. Applied Soft Computing 2024;167:112374 View
  2. Hwang S, Lee H, Lee J, Lee M, Koyanagi A, Smith L, Rhee S, Yon D, Lee J. Machine Learning–Based Prediction for Incident Hypertension Based on Regular Health Checkup Data: Derivation and Validation in 2 Independent Nationwide Cohorts in South Korea and Japan. Journal of Medical Internet Research 2024;26:e52794 View
  3. Roggendorf P, Volkov A. Framework for detecting, assessing and mitigating mental health issue in the context of online social networks: a viewpoint paper. International Journal of Health Governance 2025;30(1):118 View
  4. Shang Y. Enabling the upgrading of security emergency technology in the AI era. Safety Emergency Science 2025;1(1):9590003 View
  5. Jain R, Mungamuri S, Garg P. Redefining precision medicine in hepatocellular carcinoma through omics, translational, and AI-based innovations. The Journal of Precision Medicine: Health and Disease 2025;1:100003 View
  6. Soroush A, Sabnis S, Mehta S, Siddique S. Impact of Artificial Intelligence on the Gastroenterology Workforce and Practice. Clinical Gastroenterology and Hepatology 2025;23(9):1472 View
  7. Shaik T, Tao X, Xie H, Li L, Higgins N, Velásquez J. Towards Transparent Deep Learning in Medicine: Feature Contribution and Attention Mechanism-Based Explainability. Human-Centric Intelligent Systems 2025;5(2):209 View
  8. Vivek K, Papalois V. AI and Machine Learning in Transplantation. Transplantology 2025;6(3):23 View
  9. Sun J. Towards reproducible and high-impact machine learning in health: an editorial. Machine Learning: Health 2025;1(1):010201 View
  10. Ferri P, Sáez C, Félix-De Castro A, Sánchez-Cuesta P, García-Gómez J. An end-to-end solution for out-of-hospital emergency medical dispatch triage based on multimodal and continual deep learning. Artificial Intelligence in Medicine 2025;170:103264 View
  11. Zendehbad S, Ghasemi J, Khodadad F. Trustworthy AI in Telehealth: Navigating Challenges, Ethical Considerations, and Future Opportunities for Equitable Healthcare Delivery. Healthcare Technology Letters 2025;12(1) View
  12. Amalakanti S, Avula V, Jillella J. Advances, opportunities, and challenges of using modern artificial general intelligence and artificial intelligence-generated content technologies in depression and related disorders – Systematic review. Archives of Mental Health 2025 View
  13. Salimparsa M, Sedig K, Lizotte D, Abdullah S, Chalabianloo N, Muanda F. Explainable AI for Clinical Decision Support Systems: Literature Review, Key Gaps, and Research Synthesis. Informatics 2025;12(4):119 View

Books/Policy Documents

  1. Shukla A. Secure and Resilient Digital Transformation of Healthcare. View